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New MILES paper in TMLR

Posted on 11 janvier 2025 by croyer

The paper Differentially Private Gradient Flow based on the Sliced Wasserstein Distance, authored by Ilana Sebag, Muni Sreenivas Pydi, Jean-Yves Franceschi (Criteo AI Lab), Alain Rakotomamonjy (Criteo AI Lab), Mike Gartrell (Sigma Nova), Jamal Atif and Alexandre Allauzen, has been accepted in Transactions on Machine Learning Research.

Congratulations!

Posted in Non classé
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